Many sellers provide a broad spectrum of product configuration options with their product offerings, and allow a customer to individually configure desired options when buying the products. While such capability can provide flexibility in purchasing transactions, with so many options, the shopping customer must search over each configuration to find the product that best meets the customer's preferences. To the customer, this can be a daunting and time-consuming task. The difficulty is compounded when the querying and searching for the available products and their options involve web-based lookups. Often customers give up and look elsewhere. This results in lost sales for the seller.
The sellers usually are interested in promoting products that they can supply easily and are profitable. To date, there is no known methodology—for intelligently determining personalized sales recommendations for the substitutes to configurable or configured products—which concurrently takes into account both the customer preferences and the seller's interests.